Dear Wolfgang,
I do have protein count data for 40 people (so no replicate). These are
healthy people, no grouping. The goal is to look at similarity/dissimilarity
of the 40 samples based on protein count (differential expression IF
POSSIBLE) AND clustering of the proteins. As you said, clustering of samples
can be done with the section "Sample Clustering" of the vignette. How would
I go for clustering the proteins and look for differential expression (IF
POSSIBLE).

Thanks,
Yolande

On Mon, Apr 4, 2011 at 5:11 AM, Wolfgang Huber <whuber@embl.de> wrote:

> Dear Yolande
>
> Thanks. Can you clarify what you want to do:
> - per gene: ANOVA like estimation of effects in a factorial design
> - per sample: clustering or classification of samples based on overall
> (dis)similarity of expression profiles?
>
> From your post, I assume it's the latter. This is described in Section
> "Sample Clustering" of the vignette.
>
> (For the former, there are the functions nbinomFitGLM and nbinomGLMTest,
> but these will with the current implementation of DESeq only work if each
> cell of the design is replicated.)
>
>        Thank you and best wishes
>        Wolfgang
>
> Yolande Tra scripsit 04/04/11 00:49:
>
>>  Dear list members,
>>
>> I would like to know if it is possible to use deseq for data with multiple
>> groups (more than two) with no replicates. I went through the vignette but
>> it only illustrates the case for two groups with no replicates. If it is
>> not
>> possible for the moment, do you know a method to study
>> similarity/dissimilarity of gene/protein count data based on multiple
>> groups
>> with no replicates.
>>
>> I appreciate your feedback.
>>
>> Yolande
>>
>>        [[alternative HTML version deleted]]
>>
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>
>
> --
>
>
> Wolfgang Huber
> EMBL
> http://www.embl.de/research/units/genome_biology/huber
>
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